Dynamic monitoring of blood oxygen saturation value is an important method for the prevention and treatment of chronic cardiovascular disease. In order to meet the design requirements of wearable mobile medical, this paper uses the main controller to read, filter, and calculate pulse rate and blood oxygen value, and saturate the pulse signal and blood oxygen through the Bluetooth low-power module. The degree value and pulse rate value are transmitted to the Android smartphone, and the APP on the Android phone side manages the user’s physiological parameters and establishes a personal health file. Monitoring of blood oxygen saturation in a dynamic environment can be affected by severe motion disturbances. Aiming at this problem, this paper proposes a new adaptive cancellation algorithm based on adaptive filtering. Based on the interference analysis of the photoelectric volume pulse wave signal in a dynamic environment, this paper uses the envelope information of the PPG (Photoplethysmography) signal to extract the AC component of the photoelectric volume pulse wave signal, and construct interference-related signals as reference signals and perform adaptive filtering to suppress motion interference. The adaptive cancellation algorithm proposed in this paper performs digital signal processing on the collected original information and analyzes the calculation results. Comparing the calculated results with those of the DST (Discrete Saturation Transform) signal extraction technology, the effectiveness of the algorithm in eliminating motion interference is verified, and the anti-interference ability and time complexity of the algorithm under severe motion are verified.

动态监测血氧饱和度值是预防和治疗慢性心血管疾病的重要方法。为了满足可穿戴移动医疗的设计要求，本文使用主控制器读取，过滤和计算脉搏率和血氧值，并通过蓝牙低功耗模块使脉搏信号和血氧饱和。度值和脉搏率值被传输到Android智能手机，Android手机端的APP管理用户的生理参数并建立个人健康档案。在动态环境中监测血氧饱和度会受到严重运动干扰的影响。针对这一问题，本文提出了一种新的基于自适应滤波的自适应抵消算法。在动态环境下对光电体积脉搏波信号进行干扰分析的基础上，利用PPG（Photoplethysmography）信号的包络信息提取光电体积脉搏波信号的交流分量，并构造与干扰有关的信号为参考信号并执行自适应滤波以抑制运动干扰。本文提出的自适应抵消算法对采集到的原始信息进行数字信号处理，并对计算结果进行分析。将计算结果与DST（离散饱和变换）信号提取技术进行比较，验证了该算法消除运动干扰的有效性，